Date of Award

12-11-2025

Degree Type

Thesis

Degree Name

Master of Science (M.S.)

First Advisor

Amir Shirkhodaie

Abstract

The use of electrical vertical takeoff and landing (eVTOL) aircraft to provide efficient, high-speed, on-demand air transportation within a metropolitan area is an increasingly popular topic, which is expected to bring fundamental changes to cities. The concept of Urban Air Mobility (UAM) has the potential to make meaningful door-to-door trip time savings compared with other transportation. The capability to manage many of these eVTOL aircraft safely in a congested urban area presents an unprecedented challenge in air traffic management. In order to enable safe and efficient autonomous on-demand free flight operations in UAM, a computational guidance algorithm with collision avoidance capability is designed and analyzed. This study explores the challenges and solutions associated with (UAM), with a particular emphasis on identifying and mitigating operational disruptions such as emergencies, system failures, and environmental challenges in unmanned aerial vehicle (UAV) systems. The creation of strong emergency landing procedures suited for urban settings is a major priority. This research integrates mathematical technique-based anomaly algorithm detection methods, ensuring early threat identification and mitigation. It particularly explores collision-free UAM operations, utilizing mathematical models to predict and evaluate outcomes. To validate the proposed methodologies. We employ IRIS software’s virtual environment modeling and simulation software to simulate the diverse operational scenarios to determine the UAV’s real-time to avoid the UAM collisions. These simulations provide critical insights into the collision dynamics and operational requirements for safe and efficient UAM integration.

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